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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 3-RES-JB
    11. 8239
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    INDEX
    Explanations

    mentions of the term "Michelin" with varying degrees of relevance or specificity

    oai_token-act-pair · gpt-3.5-turbo

    references to Michelin ratings or the Michelin Guide

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Balt
    -0.73
    İĭ
    -0.70
    interrupted
    -0.70
     rook
    -0.65
    ðĿ
    -0.64
     erect
    -0.63
    oran
    -0.62
    itars
    -0.62
    ually
    -0.62
     Vaj
    -0.61
    POSITIVE LOGITS
    tti
    1.09
    lli
    1.02
    tta
    0.99
    tto
    0.93
    lla
    0.90
    enne
    0.89
    cles
    0.85
    erno
    0.84
    vine
    0.82
    otle
    0.81
    Activations Density 0.011%

    No Known Activations